Usefulness of postsystolic shortening and early systolic lengthening to detect reduced myocardial viability and predict future cardiovascular events in ST-segment elevation myocardial infarction

doi:10.21203/rs.3.rs-2493734/v1

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Usefulness of postsystolic shortening and early systolic lengthening to detect reduced myocardial viability and predict future cardiovascular events in ST-segment elevation myocardial infarction

https://doi.org/10.21203/rs.3.rs-2493734/v1

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Purpose: Postsystolic shortening (PSS) and early systolic lengthening (ESL) which represent asynchrony in ischemic myocardium can provide prognostic information in patients with ST-segment elevation myocardial infarction (STEMI). We aimed to investigate the potential of PSS and ESL to detect reduced myocardial viability and investigate the comparative prognostic value of PSS and ESL in patients with STEMI after primary PCI.

Methods: We prospectively enrolled 198 patients with STEMI who underwent primary percutaneous coronary intervention. All patients took a speckle tracking echocardiographic examination and myocardial contrast echocardiography a median of 3 days after the percutaneous coronary intervention. Early systolic strain index (ESI), postsystolic strain index (PSI) and myocardial perfusion score index (MPSI) were calculated. The end point was major adverse cardiovascular events (MACE), a composite of all-cause death, unstable angina, heart failure, non-fatal recurrent myocardial infarction, stroke, and complex ventricular arrhythmia.

Results: Reduced myocardial viability was defined as MPSI >1. Patients with category of MPSI >1.5 increased signifcantly with increasing tertiles of PSI (1.5% vs 7.6% vs 31.8%, p <0.001) and ESI (3.0% vs 12.1% vs 25.8%, p <0.001), and the highest tertile of PSI remained significantly associated with a higher MPSI in adjusted logistic regression model (b=1.00, 95% CI, 0.25-1.75; p=0.010). Areas under the curve for PSI and ESI to determine a MPSI >1 was 0.745 and 0.704 in ROC analysis. During a median follow-up of 9.0 months (interquartile range [IQR], 6.0-12.0 months), 39 (19.7%) patients suffered MACE. PSI and ESI remained predictors of MACE in adjusted cox regression models. In ROC analysis, IDI and NRI of PSI were significantly higher compared to GLS while ESL didn’t.

Conclusion: In patients with STEMI after primary PCI, PSS and ESL provides diagnostic information on reduced myocardial viability and offers prognostic information oncardiovascular events. Additionally, PSS emerged as independent predictor of mid- and long-term MACE with superior prognostic validity compared to GLS and ESL.

two-dimensional speckle tracking echocardiography

myocardial contrast echocardiography

postsystolic shortening

early systolic lengthening

myocardial infarction

myocardial viability

echocardiography

Increased risk of subsequent cardiovascular events was observed in patients with ST-segment-elevation myocardial infarction (STEMI) [1-4]. Prospective risk stratification remains a core challenge in STEMI patients and is crucial to guide treatment strategies and improve outcomes. With regard to risk stratification of acute myocardial infarction, it is important to evaluate the degree and extent of residual myocardial viability [5]. Myocardial contrast echocardiography (MCE) can reflect the condition of myocardial microcirculation by myocardial perfusion, which is a reliable method to assess myocardial viability [6-8].

Postsystolic shortening (PSS) and early systolic lengthening (ESL) considered to be sensitive parameters of myocardial ischemia [9-12] and ischemic memory [13], can be easily analyzed by STE. PSS is defined as a delayed contraction after aortic valve closure and ESL is defined as a lengthening in early systole [14] (Figure 1). Both patterns represent a paradoxical deformation or asynchronous movement of the myocardium [11,15], and they have been demonstrated to be independent predictors of cardiovascular events in STEMI patients after primary PCI [16-18]. However, it has been controversial that whether PSS is a marker of cardiac viability or not [19,20], and no study has investigated the utility of ESL in myocardial viability. Since PSS and ESL occur in ischemic myocardium and are associated with cardiovascular events, we hypothesis that PSS and ESL can be used to detect reduced myocardial viability. The aim of this study was to determine the potential of PSS and ESL in detecting reduced myocardial viability and investigate the comparative prognostic value of PSS and ESL in patients with STEMI after primary PCI.

Population

We prospectively enrolled 198 patients with STEMI from June 2021 to March 2022 who were treated with primary PCI at Renmin Hospital of Wuhan University. All patients met the following inclusion criteria: 1) at least 2 contiguous leads of ≥ 2 mm (0.2 mV) in men or ≥ 1.5 mm (0.15 mV) in women or of ≥ 1 mm (0.1 mV) in the limb leads, 2) > 30 minutes and < 24 hours after onset of chest pain, 3) had a significant increase in troponin I (TnI) (> 0.04 ng/ml), 4) underwent echocardiographic examination a median of 3 days after primary PCI. Patients with poor image quality were excluded. Baseline data were included on inclusion. The study was approved by the ethical committee of Renmin Hospital of Wuhan University and all patients signed the informed consent. This study was listed at ClinicalTrials.gov (ID: WDRY2020-K189).

Definition

Patients with BP ≥ 140/90mmHg or taking antihypertensive drugs were categorized as HBP. Diabetes mellitus was defined as nonfasting plasma glucose ≥ 11.1 mmol/L, fasting glucose ≥ 7 mmol/L, or use of antidiabetic medication. The culprit vessel was determined by coronary angiography, and three-vessel disease was defined as the stenosis of left anterior descending artery (LAD), left circumflex artery (LCx) and right coronary artery (RCA) is all severe or above.

Echocardiography

Transthoracic echocardiography was performed within a median of 3 days (IQR, 2–4 days) after the primary PCI, using ultrasound machines (EPIQ 7C, Philips Healthcare, Massachusetts, USA) with a 1.0–5.0 MHz transducer (S5-1). Images were stored and analyzed off-line using TOMTEC software (TOMTEC Imaging Systems GmbH, Unterschleissheim, Germany) by a single investigator, who was blinded to all clinical information and end point events.

1) Transthoracic echocardiography.

Transthoracic echocardiography was performed according to contemporary guidelines from the American Society of Echocardiography [21]. LVEF was obtained using Simpson’s biplane method. Wall motion score index (WMSI) was estimated by the 16-segment international model [22]. Inflow between the mitral valve leaflets was measured by pulsed-wave Doppler to obtain E (early diastolic filling), A (late diastolic filling) and E/A-ratio. Pulsed-wave tissue-Doppler was sampled at the mitral annulus in the septal wall in the apical 4-chamber view to obtain the peak early diastolic longitudinal mitral annular velocity (e), and then the E/e-ratio was calculated.

2) Speckle tracking echocardiography.

Two-dimensional STE was performed in the apical 2-, 3-, and 4-chamber views with the image frame rate > 50 Hz. We identified the endocardial and epicardial border of left ventricle in end-systole, and the software automatically tracked the gray-scale speckles. The investigator could manually adjust the region of interest to ensure correct tracking. The software calculated and provided an estimate of the global longitudinal strain (GLS), global circumferential strain (GCS) and global radial strain (GRS) by the 16-segment model. Information on PSS and ESL was derived from the strain curve of each segment. The early systolic strain index (ESI) derived from ESL was calculated as follows: ESL amplitude/maximal strain amplitude during systole. The postsystolic strain index (PSI) derived from PSS was calculated as follows: PSS amplitude/maximal strain amplitude during the cardiac cycle (Fig. 2). When PSS and ESL are not observed, the PSI and ESI values take zero. PSI and ESI was calculated as the average value from all 16 segments. As no previous study has investigated the ability of PSS combined with ESL to predict clinical outcomes, we divided patients into three groups based on the median levels of PSI and ESI.

3) Myocardial contrast echocardiography.

MCE perfusion imaging was performed by multi-pulse amplitude-modulation imaging at a mechanical index (MI) of 0.18 in the apical 2-, 3-, and 4-chamber views. Overall gain was adjusted to levels just under those that produced background myocardial speckle. SonoVue (Bracco Research SA, Geneva, Switzerland) was used as ultrasonic enhancing agent (UEA). UEA was reconstituted in 5 mL of normal saline to form a microbubble suspension and was diluted to 30 mL total volume in normal saline. The mean infusion rate was 3.5-4 ml/min. A transient high MI (1.1–1.3) flash (10 frames) was applied to destroy microbubbles, after which replenishment imaging was digitally acquired (10 to 15 cardiac cycles) in each view with a frame rate > 25 Hz. The perfusion of segments was graded as follows: myocardial segmental replenishment within 4 sec (normal), 1; delays in contrast replenishment but normal plateau intensity (delayed), 2; both delays in replenishment and reduced plateau intensity (microvascular obstruction), 3 [23]. 17-myocardial segment model was used and myocardial perfusion score index (MPSI) was calculated as the average value obtained from all 17 myocardial segments, thus MPSI can represent the extent and degree of residual infarction, and therefore it reflects the residual myocardial viability [8, 24]. Normal myocardial viability was defined as MPSI = 1 and reduced myocardial viability was defined as MPSI > 1.

Follow-up

Outcomes were determined from reviews of clinic visits and telephone interviews, which were performed at 1, 3, 6, and 12 months for each participant. The endpoint was major adverse cardiovascular events (MACE), consisting of all-cause death, hospital admission for unstable angina, hospital admission for heart failure, non-fatal recurrent myocardial infarction, stroke and complex ventricular arrhythmia.

Statistical analyses

All statistical analyses were performed using EmpowerStats software (X&Y solutions, Inc. Boston MA). Continuous data are presented as mean ± standard deviation or median (interquartile range). Categorical variables are presented as count (percentage). The PSI and ESI displayed nongaussian distributions that were successfully converted to a normal distribution using a square root transformation. Patients were divided into different groups according to median levels of PSI and ESI. Differences between groups with gaussian and nongaussian distributed variables were compared using Student t test and the Kruskal-Wallis test, respectively. Prespecified Cox proportional hazard models were used to calculate univariable and multivariable hazard ratios (HRs) and 95% confidence interval (CI) that we adjusted as follows: age, gender, diabetes, hypertension, Killip class, Peak TnI, BNP, LVEF and E/A. Kaplan-Meier curves were plotted to construct the cumulative survival curves between tertiles of PSI and ESI. Logistic regression models were used to evaluate the association between PSI, ESI and MPSI that we adjusted as follows: age, gender, diabetes, hypertension, Killip class, Peak TnI, BNP, LVEF and E/A. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic accuracy of PSI and ESI to detect MPSI > 1 and compare the discrimination power of PSI and ESI to GLS for MACE at 6 and 9 months. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) based on logistic regression were calculated to evaluate improved predictive ability of PSI and ESI to GLS. We also calculated C-index and area under the receiver operating characteristic curve (AUC) to evaluate the discrimination of different parameters. ROC analysis was also utilized to calculate the sensitivity and specificity at optimal cutoff point based on the Youden index maximization principle for different models. The difference was statistically significant with P < 0.05.

Baseline Clinical Characteristics.

A total of 198 patients were included in the study cohort. During a median follow-up period of 9.0 months (IQR, 6.0–12.0 months), 39 (19.7%) MACE cases were observed (all-cause death in 5 patients, hospital admission for unstable angina in 10 patients, hospital admission for heart failure in 16 patients, non-fatal recurrent myocardial infarction in 5 patients, stroke in 2 patients, and complex ventricular arrhythmia in 1 patient). The mean age of the cohort was 60.9 years, 81.3% were males, 58.1% had hypertension, and 28.8% had diabetes mellitus. Patients were divided into 4 groups according to median levels of PSS (13.91%, IQR 6.72–24.12) and ESL (4.53%, IQR 1.02–10.99). The patients with PSI and ESI levels below median were assigned to the Group 1, the patients with ESI above but PSI below median were assigned to the Group 2, the patients with PSI above but ESI below median were assigned to the Group 3, the patients with both PSI and ESI above median were assigned to Group 4. Patients with higher levels of PSI and ESI were more frequently to have left anterior descending artery as the culprit vessel, underwent intra-aortic balloon pump therapy, and presented with higher levels of Killip class, B-type natriuretic peptide and peak troponin I. As well, the occurrence of high-value PSS and ESL had affected other echocardiographic parameters in terms of lower LVEF, GLS, GCS and GRS, and increased values of WMSI (Table 2).

Table 1

Baseline characteristics categorized by median PSI and ESI levels.
Variable	All (n = 198)	Group 1 (n = 75)	Group 2 (n = 24)	Group 3 (n = 24)	Group 4(n = 75)	P-value
Clinical
Age, y	60.9 ± 11.4	60.3 ± 10.6	60.2 ± 13.4	60.0 ± 12.7	62.1 ± 11.1	0.727
Men, n (%)	161 (81.31%)	62 (82.7%)	20 (83.3%)	21 (87.5%)	58 (77.3%)	0.673
Smoker, n (%)	93 (46.97%)	41 (54.7%)	10 (41.7%)	10 (41.7%)	32 (42.7%)	0.410
Alcohol, n (%)	33 (16.67%)	15 (20.0%)	2 (8.3%)	2 (8.3%)	14 (18.7%)	0.200
Hypertension, n (%)	115 (58.08%)	42 (56.0%)	15 (62.5%)	9 (37.5%)	49 (65.3%)	0.106
Diabetes mellitus, n (%)	57 (28.79%)	19 (25.3%)	5 (20.8%)	11 (45.8%)	22 (29.3%)	0.204
Hyperlipermia, n (%)	81 (40.91%)	31 (41.3%)	10 (41.7%)	8 (33.3%)	32 (42.7%)	0.879
Arrhythmia, n (%)	37 (18.69%)	13 (17.3%)	5 (20.8%)	3 (12.5%)	16 (21.3%)	0.774
SBP, mmHg	124.3 ± 20.4	126.0 ± 19.8	125.5 ± 12.7	121.3 ± 24.2	123.2 ± 21.8	0.731
DBP, mmHg	76.5 ± 13.3	76.6 ± 14.8	78.6 ± 7.9	75.5 ± 10.3	76.1 ± 14.1	0.849
Heart rate, bpm	81.7 ± 15.5	79.1 ± 14.8	79.5 ± 11.7	86.1 ± 18.4	83.5 ± 15.8	0.129
Killip class						< 0.001
1	79 (39.90%)	45 (60.0%)	12 (50.0%)	7 (29.2%)	15 (20.0%)
2	55 (27.78%)	19 (25.3%)	3 (12.5%)	10 (41.7%)	23 (30.7%)
3	29 (14.65%)	7 (9.3%)	4 (16.7%)	2 (8.3%)	16 (21.3%)
4	35 (17.68%)	4 (5.3%)	5 (20.8%)	5 (20.8%)	21 (28.0%)
eGFR, ml/min	90.6 ± 22.6	90.3 ± 20.1	91.6 ± 24.9	87.7 ± 27.3	91.6 ± 23.0	0.895
Peak TnI, ng/ml	41.0 ± 15.5	35.8 ± 17.6	40.4 ± 15.2	41.8 ± 16.9	46.3 ± 10.6	< 0.001
BNP, pg/ml, ⋅10²	12.5 (6.3–25.5)	9.1 (4.1–19.9)	11.0 (7.4–17.6)	12.1 (8.3–28.0)	19.4 (7.9–36.3)	0.001
Invasive procedure
IABP, n (%)	27 (13.64%)	4 (5.3%)	3 (12.5%)	3 (12.5%)	17 (22.7%)	0.008
Multivessel disease, n (%)	78 (39.4%)	26 (34.7%)	9 (37.5%)	10 (41.7%)	33 (44.0%)	0.544
Culprit vessel, n (%)						< 0.001
LAD	103 (52.02%)	23 (30.7%)	9 (37.5%)	17 (70.8%)	54 (72.0%)
LCx	34 (17.17%)	17 (22.7%)	7 (29.2%)	2 (8.3%)	8 (10.7%)
RCA	61 (30.81%)	35 (46.7%)	8 (33.3%)	5 (20.8%)	13 (17.3%)
Symptom to balloon, h	6.0 (3.0–12.0)	5.0 (3.0–13.0)	5.5 (2.8–16.0)	7.5 (3.0–24.0)	7.0 (4.0–12.0)	0.758
Echocardiography
LVEF, %	50.8 ± 8.2	56.1 ± 5.3	51.2 ± 8.3	49.1 ± 6.5	46.0 ± 7.8	< 0.001
E, cm/s	65.3 ± 23.1	73.3 ± 25.8	63.6 ± 20.6	58.1 ± 17.6	60.2 ± 20.5	0.001
A, cm/s	84.5 ± 18.78	85.6 ± 18.8	80.7 ± 20.5	85.1 ± 16.1	84.4 ± 19.1	0.753
E/A-ratio	0.8 ± 0.4	0.9 ± 0.3	0.9 ± 0.5	0.7 ± 0.2	0.8 ± 0.5	0.276
E/e-ratio	11.4 ± 3.6	11.2 ± 3.1	11.0 ± 3.5	11.0 ± 3.1	11.9 ± 4.1	0.516
GLS, %	-10.8 ± 4.2	-13.6 ± 3.1	-12.3 ± 3.7	-8.9 ± 2.6	-8.1 ± 3.5	< 0.001
GCS, %	-15.8 ± 5.6	-18.4 ± 4.9	-15.5 ± 4.4	-14.4 ± 5.3	-13.7 ± 5.8	< 0.001
GRS, %	16.2 ± 7.6	18.4 ± 7.7	18.3 ± 8.8	14.3 ± 6.8	13.9 ± 6.5	< 0.001
WMSI	1.3 ± 0.3	1.1 ± 0.1	1.3 ± 0.3	1.4 ± 0.3	1.5 ± 0.3	< 0.001
MPSI	1.2 ± 0.2	1.1 ± 0.1	1.2 ± 0.2	1.2 ± 0.3	1.3 ± 0.3	< 0.001
Continuous data are presented as mean ± standard deviation or median (interquartile range), categorical variables are presented as count (%). SBP: systolic blood pressure; DBP: diastolic blood pressure; bpm: beats per minute; eGFR: estimated glomerular filtration rate; Peak TnI: peak troponin I; BNP: B-type natriuretic peptide; IABP: intra-aortic balloon pump; LAD: left anterior descending artery; LCx: left circumflex artery; RCA: right coronary artery; LVEF: left ventricular ejection fraction; E, transmitral peak velocity of early diastolic filling; A, transmitral peak velocity of atrial diastolic filling; e: average peak early diastolic longitudinal mitral annular velocity; GLS: global longitudinal strain; GCS: global circumferential strain; RS: radial strain; WMSI: wall motion score index; MPSI: myocardial perfusion score index.

Table 2

Logistic regression models assessing the association between PSI, ESL and MPSI.
Association with MPSI⋅10	Unadjusted		Adjusted*
Association with MPSI⋅10	β (95%CI)	P-value	β (95%CI)	P-value
PSI
1st tertile	Ref.		Ref.
2nd tertile	1.25 (0.54, 1.95)	< 0.001	0.15 (-0.51, 0.80)	0.665
3rd tertile	3.08 (2.38, 3.79)	< 0.001	1.00 (0.25, 1.75)	0.010
ESI
1st tertile	Ref.		Ref.
2nd tertile	0.80 (0.05, 1.55)	0.038	0.37 (-0.24, 0.98)	0.234
3rd tertile	2.46 (1.71, 3.21)	< 0.001	0.44 (-0.25, 1.13)	0.211
*Adjusted age, gender, diabetes, hypertension, Killip class, Peak TnI, BNP, LVEF and E/A. PSI, postsystolic strain index; ESI: early systolic strain index; MPSI: myocardial perfusion score index.

Association Between PSS and ESL Level and myocardial viability

Categories of MPSI increased signifcantly with increasing tertiles of PSI and ESI (p < 0.001; Fig. 3A and 3B). In unadjusted logistic regression models, increasing tertiles of PSI (2nd tertile, β = 1.25, 95% CI, 0.54–1.95; p < 0.001; 3rd tertile, β = 3.08, 95% CI, 2.38–3.79; p < 0.001) and ESI (2nd tertile, β = 0.80, 95% CI, 0.05–1.55; p = 0.038; 3rd tertile, β = 2.46, 95% CI, 1.71–3.21; p < 0.001) were each significantly associated with increased MPSI. However, after adjustment for age, gender, diabetes, hypertension, Killip class, Peak TnI, BNP, LVEF and E/A, only the highest tertile of PSI (β = 1.00, 95% CI, 0.25–1.75; p = 0.010) was significantly associated with a higher MPSI (Table 2). The AUCs of PSI and ESI respectively to detect MPSI > 1 was 0.745 and 0.704, with a sensitivity of 76% and 59% and specificity of 69% and 79%, respectively (Table 3).

Table 3

Diagnostic accuracy for PSI and ESI to determine a myocardial perfusion score index > 1.
	AUC	Sensitivity (%)	Specificity (%)	Cut-off value
PSI	0.745	76	69	10.63
ESI	0.704	59	79	5.70
PSI, postsystolic strain index; ESI: early systolic strain index; AUC: area under the receiver operating characteristic curve.

Association Between PSS and ESL Level and Clinical Outcomes.

Clinical characteristics of the patients stratified by tertiles of PSS and ESL levels respectively are shown in Supplemental Tables 1 and 2. The PSI (HR, 2.21 per 1% increase; 95% CI, 1.72–2.83; p < 0.001) and ESI (HR, 1.63 per 1% increase; 95% CI, 1.37–1.94; p < 0.001) were significantly associated with MACE. After adjustment for age, gender, diabetes, hypertension, Killip class, Peak TnI, BNP, LVEF and E/A, PSI (HR, 1.97 per 1% increase; 95% CI, 1.43–2.71; p < 0.001) and ESI (HR, 1.37 per 1% increase; 95% CI, 1.08–1.73; p = 0.010) remained independent predictors of MACE (Table 4). Kaplan-Meier analysis revealed the incrementally increased risk of MACE with increasing tertiles of the PSI and ESI (all log-rank p < 0.001). The highest tertile of the PSI (Fig. 4A) and ESI (Fig. 4B) yielded the highest risk of MACE. Compared with patients in Group 1 (low levels of PSI and ESI), Group 3 (high PSI level and low ESI level) (HR, 7.70; 95% CI, 1.41–42.06; p = 0.018) was significantly associated with increased risk of MACE while Group 2 (high ESI level and low PSI level) (HR, 3.32; 95% CI, 0.47–23.57; p = 0.231) was not. However, only Group 4 (high levels of PSI and ESI) (HR, 6.21; 95% CI, 1.26–30.55; p = 0.025) remained predictor of MACE after adjustment (Table 4).

Table 4

PSI and ESI as Predictors of MACE.
Risk of MACE	Unadjusted		Adjusted*
Risk of MACE	HR (95% CI)	P-value	HR (95% CI)	P-value
PSI and ESI independently as Predictors of MACE
PSI, %	2.21 (1.72, 2.83)	< 0.001	1.97 (1.43, 2.71)	< 0.001
ESI, %	1.63 (1.37, 1.94)	< 0.001	1.37 (1.08, 1.73)	0.010
Comparison of PSI and ESI as Predictors of MACE
Group 1	Ref.		Ref.
Group 2	3.32 (0.47, 23.57)	0.231	0.69 (0.06, 7.36)	0.756
Group 3	7.70 (1.41, 42.06)	0.018	4.73 (0.83, 26.99)	0.081
Group 4	18.42 (4.41, 77.01)	< 0.001	6.21 (1.26, 30.55)	0.025
*Adjusted age, gender, diabetes, hypertension, Killip class, Peak TnI, BNP, LVEF and E/A. PSI, postsystolic strain index; ESI: early systolic strain index; MACE: major adverse cardiovascular event; HR: hazard ratio; CI: confidence interval; Group 1: patients with PSI and ESI levels below median; Group 2: patients with ESI above but PSI below median; Group 3: patients with PSI above but ESI below median; Group 4: patients with PSI and ESI above median.

Receiver-Operator Characteristic Curve Analysis.

In order to evaluate the prognostic value of PSS, ESL and GLS, ROC analysis was used to assess the discrimination (Table 5). All three parameters exhibited good performance, with AUCs > 0.7 for predicting MACE at 6 months, 9 months and a year, among which PSI performed the best with AUC > 0.8. C-index were 0.752 (CI 95% 0.67–0.84), 0.749 (CI 95% 0.67–0.82) and 0.798 (CI 95% 0.73–0.86) for GLS, ESI and PSI, respectively. When comparing PSI to GLS, both IDI and NRI were significantly improved for predicting MACE and at 9 months (IDI, 0.108; 95% CI, 0.005–0.196; p = 0.040; NRI, 0.489; 95% CI, 0.132–0.666; p = 0.020) and a year (IDI, 0.118; 95% CI, 0.019–0.222; p = 0.027; NRI, 0.404; 95% CI, 0.016–0.656; p = 0.040); NRI (NRI: 0.378; 95% CI, 0.018–0.554; p = 0.027) improved significantly for predicting MACE and at 6 months though IDI (IDI: 0.073; 95% CI, -0.028-0.167; p = 0.113) did not. However, neither IDI nor NRI was significant when comparing ESI to GLS for predicting MACE at 6 months, 9 months and a year.

Table 5

Comparison of PSI, ESI vs GLS for the discrimination and diagnostic efficiency of MACE at 6 months, 9 months and a year after STEMI.
	GLS	ESI	PSI
C-index	0.752	0.749	0.798
6-month
AUC	0.746	0.741	0.817
IDI	Ref	-0.021 (-0.103-0.065)	0.073 (-0.028-0.167)
NRI	Ref	-0.171 (-0.366-0.175)	0.378 (0.018–0.554)*
Sensitivity	0.77	0.84	0.88
Specificity	0.65	0.58	0.61
9-month
AUC	0.757	0.741	0.830
IDI	Ref	-0.018 (-0.112-0.075)	0.108 (0.005–0.196)*
NRI	Ref	-0.141 (-0.395-0.212)	0.489 (0.132–0.666)*
Sensitivity	0.77	0.85	0.83
Specificity	0.67	0.57	0.68
a-year
AUC	0.765	0.727	0.827
IDI	Ref	-0.036 (-0.121-0.052)	0.118 (0.019–0.222)*
NRI	Ref	-0.245 (-0.478-0.073)	0.404 (0.016–0.656)*
Sensitivity	0.83	0.78	0.90
Specificity	0.62	0.59	0.60
PSI, postsystolic strain index; ESI: early systolic strain index; GLS: global longitudinal strain; AUC, area under the receiver operating characteristic curve. IDI, integrated discrimination improvement. NRI, net reclassification improvement.
*p ≤0.05.

In this study we demonstrate the potential of PSS and ESL in detecting reduced myocardial viability. High level of PSS was independently associated with decreased viability in myocardium. Additionally, both parameters were independent predictors of adverse cardiovascular events, and PSS emerged as independent predictor of mid- and long-term MACE with superior prognostic validity compared to GLS and ESL.

The association between postsystolic shortening, early systolic lengthening and myocardial viability

Occurring in patients with myocardial ischemia, PSS has been a topic of debate about whether it is a marker of myocardial viability or not. The former was supported by several studies in patients suffered from myocardial infarction (MI). Song et al. [19] found that PSS in the infarct territory is closely related with peri-infarction ischemia or viability detected by dobutamine stress echocardiography (DSE) in patients with anterior MI. Hosokawa et al. [25] and Eek et al. [26] found that PSS is associated with recovery of myocardial and systolic function in acute anterior MI and NSTEMI patients, which indirectly proved that PSS represents viable myocardium. However, other studies have reported that PSS is not a marker of viability. Terkelsen et al. [20] and Lim et al. [27] assessed PSS in a STEMI population and patients with chronic LV ischemic dysfunction, respectively, and found that presence of PSS is not associated with improvement in strain or wall-motion score at follow-up but may be associated to scarred segments, thus PSS is not a marker of viability. These different conclusions suggest that there remains heterogeneity on this topic. Besides PSS, ESL is a rather new marker of myocardial ischemia, and its utility for indicating myocardial viability has not been studied yet.

Our study used MCE rather than DSE for detection of viable myocardium, which has been shown to provide incremental benefit over low-dose dobutamine for predicting myocardial viability [28]. We found that there are more patients with MPSI > 1.5 in the highest tertile of PSI and ESI than in the lower tertiles (p < 0.001), which indicated that with higher levels of PSI and ESI, patients are more likely to suffer from decreased myocardial microvascular integrity. This finding suggest PSS and ESL are phenomena that occurs in myocardium with reduced viability. In addition, after adjustment in logistic regression models, only the highest tertile if PSI is associated with a higher MPSI. This suggests that high level of PSS may be determined as the independent predictor of reduced myocardial viability. Moreover, PSI and ESI showed good diagnostic accuracy of MPSI > 1 with AUCs > 0.7, 76% and 59% sensitivity and 69% and 79% specificity, respectively, which indicated that PSS and ESL can be used to detect reduction of myocardial viability. Our findings consisted with Terkelsen et al. and Lim et al.’s studies that PSS is not a marker of myocardial viability. On the contrary, our study further suggests that PSS and ESL are markers of reduced myocardial viability.

The association between postsystolic shortening, early systolic lengthening and cardiovascular events

A number of studies have investigated the predictive value of PSS or ESL. Either of them has emerged to be predictor of cardiovascular events in patients with STEMI, acute coronary syndrome, stable angina pectoris, diabetes, patients undergoing coronary artery bypass graft or in general population [17, 16, 29–34]. In our study, PSI and ESI remained predictors of MACE in adjusted cox regression models, which indicated that PSS and ESL are independent predictors of MACE in STEMI patients after primary PCI. This finding consisted with the previous studies. However, Brainin et al. [17] assessed PSS in culprit and non-exposed area, and found that PSS in culprit area is the independent predictor of heart failure but not MACE in STEMI patients. Our study used the different method by calculating PSI and ESI as the average value obtained from all 16 myocardial segments, hence allowing that each patient corresponds to only one PSS and ESL value. This may be the reason why the result of our study is different from that of Brainin’s, and future studies are needed to confirm whether PSS can independently predict heart failure or MACE. Since our findings also suggest that PSS and ESL are associated with decreased myocardial viability, this may be one of the reasons why PSS and ESL can perform as predictors of cardiovascular events in STEMI patients.

To our knowledge, no studies have compared the prognostic power of PSS and ESL. In the cox regression model of our study, patients with ESI above but PSI below median are not associated with MACE in both unadjusted and adjusted models; on the other hand, patients with PSI above but ESI below median are significantly associated with MACE in unadjusted model but not in adjusted model. It is worth noting that the p value for MACE in this group of patients (p = 0.081) remained marginally significant after adjustment, and this might be attributed to the small sample size and short follow-up. These findings suggest that PSS may be better associated with MACE than ESL did. Moreover, our study compared the discriminative prognostic power of PSS, ESL and GLS using ROC analysis. In the context of acute STEMI, GLS has been proved to be independent predictor of MACE after revascularization and has demonstrated incremental prognostic value over LVEF [35, 36]. In our study, IDI and NRI of PSS significantly increased compared to GLS for predicting MACE at 9 months and a year, which suggest that PSS may be a more powerful parameter compared with GLS in predicting mid- and long-term adverse events in patients with STEMI.

Study limitations

There are several limitations in this study. First, the enrolled sample size is relatively small. We aim to recruit more patients with STEMI in future studies. Second, as this is a single center study, a multicenter validation cohort is needed to confirm our study results. Third, we carried out the echocardiographic examination a median of 3 days after revascularization. Systolic dysfunction may not be fully manifested during this period; and measurements of ESL and PSS are known to decrease over time after ischemic events so that ESL and PSS might have occurred and disappeared before the echocardiography was performed, resulting in underestimated presence and values of ESL and PSS [13]. Lastly, as it’s a non-randomized study, the risk of potential residual confounders always exists.

In conclusion, PSS and ESL after primary PCI in patients with STEMI can be used to detect reduced myocardial viability and offers prognostic information on cardiovascular events. Additionally, PSS emerged as an independent predictor of mid- and long-term MACE with superior prognostic validity compared to GLS and ESL.

CONFLICT OF INTEREST STATEMENT

All authors declare no conflict of potential competing interests.

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No competing interests reported.

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Usefulness of postsystolic shortening and early systolic lengthening to detect reduced myocardial viability and predict future cardiovascular events in ST-segment elevation myocardial infarction

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Introduction

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Echocardiography

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Association Between PSS and ESL Level and myocardial viability

Discussion

The association between postsystolic shortening, early systolic lengthening and myocardial viability

The association between postsystolic shortening, early systolic lengthening and cardiovascular events

Study limitations

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